Alicia L. Reiner

Influence of Prescribed Fire on Ecosystem Biomass, Carbon, and Nitrogen in a Pinyon Juniper Woodland

Abstract Increases in pinyon and juniper woodland cover associated with land-use history are suggested to provide offsets for carbon emissions in arid regions. However, the largest pools of carbon in arid landscapes are typically found in soils, and aboveground biomass cannot be considered long-term storage in fire-prone ecosystems. Also, the objectives of carbon storage may conflict with management for other ecosystem services and fuels reduction. Before appropriate decisions can be made it is necessary to understand the interactions between woodland expansion, management treatments, and carbon retention. We quantified effects of prescribed fire as a fuels reduction and ecosystem maintenance treatment on fuel loads, ecosystem carbon, and nitrogen in a pinyon–juniper woodland in the central Great Basin. We found that plots containing 30% tree cover averaged nearly 40 000 kg · ha−1 in total aboveground biomass, 80 000 kg · ha−1 in ecosystem carbon (C), and 5 000 kg · ha−1 in ecosystem nitrogen (N). Only 25% of ecosystem C and 5% of ecosystem N resided in aboveground biomass pools. Prescribed burning resulted in a 65% reduction in aboveground biomass, a 68% reduction in aboveground C, and a 78% reduction in aboveground N. No statistically significant change in soil or total ecosystem C or N occurred. Prescribed fire was effective at reducing fuels on the landscape and resulted in losses of C and N from aboveground biomass. However, the immediate and long-term effects of burning on soil and total ecosystem C and N is still unclear.

Estimation procedures for understory biomass and fuel loads in sagebrush steppe invaded by woodlands

ABSTRACT. Regression equations were developed to predict biomass for 9 shrubs, 9 grasses, and 10 forbs that generally dominate sagebrush ecosystems in central Nevada. Independent variables included percent cover, average height, and plant volume. We explored 2 ellipsoid volumes: one with maximum plant height and 2 crown diameters and another with live crown height and 2 crown diameters. Dependent variables were total, live, leaf, and dead biomass. Simple, multiple, linear, and power equations were investigated. Models were chosen based on scatter plots, residual plots, and R2 and SEE values. In general, simple power equations provided the best-fit regressions. For shrubs, the ellipsoid volume computed with maximum plant height best predicted total plant weight, and the ellipsoid volume computed with the live crown height best predicted shrub foliage weight. In addition to regression equations for biomass, ratios for division of that biomass into 1-, 10-, 100-, and 1000-hour fuels were derived for common large shrubs. Regression equations were also derived to relate litter mat sizes of major shrub species to litter weights. The equations in this paper could be used to predict biomass in other areas of the Great Basin if training data were taken to validate or adjust these models.

Using field data to assess model predictions of surface and ground fuel consumption by wildfire in coniferous forests of California

Inventories of greenhouse gas (GHG) emissions from wildfire provide essential information to the state of California, USA, and other governments that have enacted emission reductions. Wildfires can release a substantial amount of GHGs and other compounds to the atmosphere, so recent increases in fire activity may be increasing GHG emissions. Quantifying wildfire emissions however can be difficult due to inherent variability in fuel loads and consumption and a lack of field data of fuel consumption by wildfire. We compare a unique set of fuel data collected immediately before and after six wildfires in coniferous forests of California to fuel consumption predictions of the first-order fire effects model (FOFEM), based on two different available fuel characterizations. We found strong regional differences in the performance of different fuel characterizations, with FOFEM overestimating the fuel consumption to a greater extent in the Klamath Mountains than in the Sierra Nevada. Inaccurate fuel load inputs caused the largest differences between predicted and observed fuel consumption. Fuel classifications tended to overestimate duff load and underestimate litter load, leading to differences in predicted emissions for some pollutants. When considering total ground and surface fuels, modeled consumption was fairly accurate on average, although the range of error in estimates of plot level consumption was very large. These results highlight the importance of fuel load input to the accuracy of modeled fuel consumption and GHG emissions from wildfires in coniferous forests.

Fuel accumulation and forest structure change following hazardous fuel reduction treatments throughout California

Altered fuel conditions coupled with changing climate have disrupted fire regimes of forests historically characterisedbyhigh-frequencyandlow-to-moderate-severityfire.Managersusefueltreatmentstoabateundesirablefire behaviour and effects. Short-term effectiveness of fuel treatments to alter fire behaviour and effects is well documented; however, long-term effectiveness is not well known. We evaluated surface fuel load, vegetation cover and forest structure beforeandaftermechanicalandfire-onlytreatmentsover8yearsacross11NationalForestsinCalifornia.Eightyearspost treatment, total surface fuel load returned to 67 to 79% and 55 to 103% of pretreatment levels following fire-only and mechanical treatments respectively. Herbaceous or shrub cover exceeded pretreatment levels two-thirds of the time 8yearsaftertreatment.Fire-onlytreatmentswarrantedre-entryat8yearsposttreatmentowingtotheaccumulationoflive and dead fuels and minimal impact on canopy bulk density. In general, mechanical treatments were more effective at reducing canopy bulk density and initially increasing canopy base height than prescribed fire. However, elevated surface fuel loads, canopy base height reductions in later years and lack of restoration of fire as an ecological process suggest that including prescribed fire would be beneficial. Additional keywords: dry mixed conifer, mechanical treatments, moist mixed conifer, prescribed fire, yellow pine.